Finding an optimized set of transformations for convexifying nonconvex MINLP problems

A4 Konferenspublikationer


Interna författare/redaktörer


Publikationens författare: Lundell, Andreas, Westerlund, Tapio
Redaktörer: Iftekhar A Karimi, Rajagopalan Srinivasan
Förlagsort: Amsterdam
Publiceringsår: 2012
Tidskrift: Computer Aided Chemical Engineering
Förläggare: Elsevier
Moderpublikationens namn: 11th International Symposium on Process Systems Engineering
Tidskriftsakronym: COMPUT-AIDED CHEM EN
Seriens namn: European Symposium on Computer Aided Process Engineering
Volym: 31
Artikelns första sida, sidnummer: 1497
Artikelns sista sida, sidnummer: 1501
Antal sidor: 5
ISBN: 978-0-444-59505-8
ISSN: 1570-7946


Abstrakt

In this paper we describe a method for obtaining sets of transformations for reformulating a mixed integer nonlinear programming (MINLP) problem containing nonconvex twice-differentiable (C-2) functions to a convex MINLP problem in an extended variable space. The method for obtaining the transformations is based on solving a mixed integer linear programming (MILP) problem given the structure of the nonconvex MINLP problem. The solution of the MILP problem renders a minimal set of transformations convexifying the nonconvex problem. This technique is implemented as an part of the alpha signomial global optimization algorithm (alpha SGO), a global optimization algorithm for nonconvex MINLP problems.


Nyckelord

global optimization, nonconvex MINLP problems, reformulation techniques, signomial functions

Senast uppdaterad 2019-15-12 vid 04:58